University of Anbar

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Network virtualization is considerably gaining attention as a solution to ossification of the Internet. However, the success of network virtualization will depend in part on how efficiently the virtual networks utilize substrate network resources. In this paper, the authors propose a machine learning-based approach to virtual network resource management. They...

The authors address the challenging and open problem of bringing together two crucial activities in data integration and data quality, i.e., transforming data using schema mappings, and fixing conflicts and inconsistencies using data repairing. This problem is made complex by several factors. Schema mappings and data repairing have traditionally been...

The analysis of high dimensional data comes with many intrinsic challenges. In particular, cluster structures become increasingly hard to detect when the data includes dimensions irrelevant to the individual clusters. With increasing dimensionality, distances between pairs of objects become very similar, and hence, meaningless for knowledge discovery. In this paper,...

Frequent Itemset Mining (FIM) is one of the most well known techniques to extract knowledge from data. The combinatorial explosion of FIM methods become even more problematic when they are applied to big data. Fortunately, recent improvements in the field of parallel programming already provide good tools to tackle this...

Since the past few years, due to the physical limitations on the speed of individual processor cores, instead of getting faster, computers are getting more parallel. This paper describes a novel approach to neighbor finding in Smoothed Particle Hydrodynamics (SPH) simulations with large dynamic range in smoothing length. This approach...

Traditionally, pattern discovery in graphs has been mostly limited to searching for frequent subgraphs, reoccurring patterns within which nodes with certain labels are frequently interconnected in exactly the same way. The authors relax this requirement by claiming that a set of labels is interesting if they often occur in each...

Software systems today are increasingly used in changing environments and expected to adapt with variable adaptation concerns. This requirement demands a systematic approach to efficiently construct system global adaptation behaviour according to the dynamic adaptation requirements. This paper presents Transformer - a framework for adaptation behaviour composition support based on...

Distributed networks typically consist of a set of nodes interconnected through a network, each equipped with a single server to process jobs. Jobs may enter the network via one or multiple central dispatchers or via the processing nodes themselves. In the former case the dispatchers will distribute the jobs among...

Due to the extreme energy requirements often found in sensor networks and the fact that these sensor networks are being used for an increasingly wide variety of applications, there currently exist many different sensor network MAC protocols each optimised for a different set of application requirements. Since these MAC protocols...

Arguably, the two main proponents of exploratory data mining research are clustering and pattern mining. Both share the aim of the field - extracting interesting, non-trivial, and previously unknown knowledge from data - yet, they are orthogonal in their approach, or at least appear so at first glance. Pattern mining,...

The results returned by a search, data mining or database engine often contains an overload of potentially interesting information. A daunting and challenging problem for a user is to pick out the useful information. In this paper, the authors propose an interactive framework to efficiently explore and (re)rank the objects...

Inductive databases integrate database querying with database mining. In this paper, the authors present an inductive database system that does not rely on a new data mining query language, but on plain SQL. They propose an intuitive and elegant framework based on virtual mining views, which are relational tables that...

When programming resource-scarce embedded smart devices the designer requires both the low-level system programming features of a language such as C and higher level capability typical of a language like Java. The choice of a particular language often implies trade offs between conflicting design goals such as performance, costs, time-to-market,...

Quantum cryptography utilizes quantum phenomena such as the no-cloning theorem and the Heisenberg uncertainty principle to achieve the goal of secure communication over quantum channels. The object of a Quantum Key Distribution (QKD) protocol is to enable Alice and Bob to securely distribute session keys that can be used for...

Today's organizations face the challenge to excel due to demanding customers. Hence, they are relying on their business processes to outperform competitors. Maturity models have been proposed to gradually assess and improve business processes. However, the proliferation of business process maturity models has complicated the practitioner's choice. This paper clarifies...

Distributed networks typically consist of a set of nodes interconnected through a network, each equipped with a single server to process jobs. Jobs may enter the network via one or multiple central dispatchers or via the processing nodes themselves. In the former case the dispatchers will distribute the jobs among...

Due to the extreme energy requirements often found in sensor networks and the fact that these sensor networks are being used for an increasingly wide variety of applications, there currently exist many different sensor network MAC protocols each optimised for a different set of application requirements. Since these MAC protocols...

Software systems today are increasingly used in changing environments and expected to adapt with variable adaptation concerns. This requirement demands a systematic approach to efficiently construct system global adaptation behaviour according to the dynamic adaptation requirements. This paper presents Transformer - a framework for adaptation behaviour composition support based on...

When programming resource-scarce embedded smart devices the designer requires both the low-level system programming features of a language such as C and higher level capability typical of a language like Java. The choice of a particular language often implies trade offs between conflicting design goals such as performance, costs, time-to-market,...

Quantum cryptography utilizes quantum phenomena such as the no-cloning theorem and the Heisenberg uncertainty principle to achieve the goal of secure communication over quantum channels. The object of a Quantum Key Distribution (QKD) protocol is to enable Alice and Bob to securely distribute session keys that can be used for...

Since the past few years, due to the physical limitations on the speed of individual processor cores, instead of getting faster, computers are getting more parallel. This paper describes a novel approach to neighbor finding in Smoothed Particle Hydrodynamics (SPH) simulations with large dynamic range in smoothing length. This approach...

Arguably, the two main proponents of exploratory data mining research are clustering and pattern mining. Both share the aim of the field - extracting interesting, non-trivial, and previously unknown knowledge from data - yet, they are orthogonal in their approach, or at least appear so at first glance. Pattern mining,...

Inductive databases integrate database querying with database mining. In this paper, the authors present an inductive database system that does not rely on a new data mining query language, but on plain SQL. They propose an intuitive and elegant framework based on virtual mining views, which are relational tables that...

The authors address the challenging and open problem of bringing together two crucial activities in data integration and data quality, i.e., transforming data using schema mappings, and fixing conflicts and inconsistencies using data repairing. This problem is made complex by several factors. Schema mappings and data repairing have traditionally been...

Frequent Itemset Mining (FIM) is one of the most well known techniques to extract knowledge from data. The combinatorial explosion of FIM methods become even more problematic when they are applied to big data. Fortunately, recent improvements in the field of parallel programming already provide good tools to tackle this...

The analysis of high dimensional data comes with many intrinsic challenges. In particular, cluster structures become increasingly hard to detect when the data includes dimensions irrelevant to the individual clusters. With increasing dimensionality, distances between pairs of objects become very similar, and hence, meaningless for knowledge discovery. In this paper,...

Traditionally, pattern discovery in graphs has been mostly limited to searching for frequent subgraphs, reoccurring patterns within which nodes with certain labels are frequently interconnected in exactly the same way. The authors relax this requirement by claiming that a set of labels is interesting if they often occur in each...

The results returned by a search, data mining or database engine often contains an overload of potentially interesting information. A daunting and challenging problem for a user is to pick out the useful information. In this paper, the authors propose an interactive framework to efficiently explore and (re)rank the objects...

Today's organizations face the challenge to excel due to demanding customers. Hence, they are relying on their business processes to outperform competitors. Maturity models have been proposed to gradually assess and improve business processes. However, the proliferation of business process maturity models has complicated the practitioner's choice. This paper clarifies...

Network virtualization is considerably gaining attention as a solution to ossification of the Internet. However, the success of network virtualization will depend in part on how efficiently the virtual networks utilize substrate network resources. In this paper, the authors propose a machine learning-based approach to virtual network resource management. They...

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